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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sat, 13 Aug 2016 12:15:14 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Aug/13/t14710869791eqyg97o6wlilrb.htm/, Retrieved Wed, 01 May 2024 18:27:28 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296503, Retrieved Wed, 01 May 2024 18:27:28 +0000

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Estimated Impact

149

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Mean versus Median] [mean vs median va...] [2016-08-11 11:22:45] [4c392b130fccc63297597dd6ffb6df17]
- RMP   [Mean Plot] [mean en meadian p...] [2016-08-11 22:10:26] [4c392b130fccc63297597dd6ffb6df17]
- RMP     [(Partial) Autocorrelation Function] [autocorrelation a...] [2016-08-11 22:42:14] [4c392b130fccc63297597dd6ffb6df17]
- RMP         [Classical Decomposition] [additief decompos...] [2016-08-13 11:15:14] [d7adcc7732e5b057da1b42af54844e1a] [Current]

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Dataseries X:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296503&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296503&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296503&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	77	NA	NA	-5.52604	NA
2	85	NA	NA	-9.99479	NA
3	85	NA	NA	3.4375	NA
4	78	NA	NA	0.546875	NA
5	89	NA	NA	8.98958	NA
6	87	NA	NA	-1.88021	NA
7	80	79.6198	84.5	-4.88021	0.380208
8	83	79.2708	84.5833	-5.3125	3.72917
9	88	98.6562	84.5	14.1563	-10.6562
10	86	77.6667	84.5417	-6.875	8.33333
11	81	84.4115	84.7083	-0.296875	-3.41146
12	94	92.3021	84.6667	7.63542	1.69792
13	79	79.1823	84.7083	-5.52604	-0.182292
14	85	75.0885	85.0833	-9.99479	9.91146
15	83	89.0208	85.5833	3.4375	-6.02083
16	81	86.1302	85.5833	0.546875	-5.13021
17	90	94.3646	85.375	8.98958	-4.36458
18	85	83.4115	85.2917	-1.88021	1.58854
19	83	80.3281	85.2083	-4.88021	2.67188
20	89	79.9792	85.2917	-5.3125	9.02083
21	94	99.6562	85.5	14.1563	-5.65625
22	80	79.0417	85.9167	-6.875	0.958333
23	82	85.9115	86.2083	-0.296875	-3.91146
24	91	94.0104	86.375	7.63542	-3.01042
25	80	80.724	86.25	-5.52604	-0.723958
26	86	75.5885	85.5833	-9.99479	10.4115
27	87	88.8125	85.375	3.4375	-1.8125
28	87	86.0469	85.5	0.546875	0.953125
29	91	94.6562	85.6667	8.98958	-3.65625
30	88	84.0365	85.9167	-1.88021	3.96354
31	77	80.8698	85.75	-4.88021	-3.86979
32	79	80.0625	85.375	-5.3125	-1.0625
33	99	99.3646	85.2083	14.1563	-0.364583
34	78	78.4167	85.2917	-6.875	-0.416667
35	88	85.0365	85.3333	-0.296875	2.96354
36	91	93.0938	85.4583	7.63542	-2.09375
37	76	80.1406	85.6667	-5.52604	-4.14062
38	81	75.7552	85.75	-9.99479	5.24479
39	88	89.1042	85.6667	3.4375	-1.10417
40	88	86.0885	85.5417	0.546875	1.91146
41	91	94.4062	85.4167	8.98958	-3.40625
42	91	83.5365	85.4167	-1.88021	7.46354
43	79	80.5365	85.4167	-4.88021	-1.53646
44	79	79.7292	85.0417	-5.3125	-0.729167
45	97	98.9062	84.75	14.1563	-1.90625
46	77	77.7917	84.6667	-6.875	-0.791667
47	86	84.4115	84.7083	-0.296875	1.58854
48	93	92.3437	84.7083	7.63542	0.65625
49	74	79.1406	84.6667	-5.52604	-5.14062
50	74	74.5885	84.5833	-9.99479	-0.588542
51	88	87.9792	84.5417	3.4375	0.0208333
52	86	85.1719	84.625	0.546875	0.828125
53	94	93.5729	84.5833	8.98958	0.427083
54	88	82.6198	84.5	-1.88021	5.38021
55	81	79.7448	84.625	-4.88021	1.25521
56	75	79.3958	84.7083	-5.3125	-4.39583
57	100	98.6979	84.5417	14.1563	1.30208
58	76	77.625	84.5	-6.875	-1.625
59	86	84.3698	84.6667	-0.296875	1.63021
60	91	92.2604	84.625	7.63542	-1.26042
61	79	78.6823	84.2083	-5.52604	0.317708
62	71	73.9635	83.9583	-9.99479	-2.96354
63	87	87.3125	83.875	3.4375	-0.3125
64	86	84.2135	83.6667	0.546875	1.78646
65	98	92.3646	83.375	8.98958	5.63542
66	83	81.2865	83.1667	-1.88021	1.71354
67	76	78.2031	83.0833	-4.88021	-2.20312
68	74	77.5208	82.8333	-5.3125	-3.52083
69	99	96.9062	82.75	14.1563	2.09375
70	72	76	82.875	-6.875	-4
71	83	82.3698	82.6667	-0.296875	0.630208
72	89	89.9271	82.2917	7.63542	-0.927083
73	79	76.6823	82.2083	-5.52604	2.31771
74	65	72.4219	82.4167	-9.99479	-7.42188
75	91	86.1875	82.75	3.4375	4.8125
76	85	83.7135	83.1667	0.546875	1.28646
77	94	92.3646	83.375	8.98958	1.63542
78	78	81.7031	83.5833	-1.88021	-3.70312
79	79	78.8698	83.75	-4.88021	0.130208
80	76	78.4375	83.75	-5.3125	-2.4375
81	105	97.9062	83.75	14.1563	7.09375
82	76	76.75	83.625	-6.875	-0.75
83	84	83.2031	83.5	-0.296875	0.796875
84	93	90.9271	83.2917	7.63542	2.07292
85	79	77.6406	83.1667	-5.52604	1.35938
86	65	73.2969	83.2917	-9.99479	-8.29688
87	91	86.7708	83.3333	3.4375	4.22917
88	82	83.7969	83.25	0.546875	-1.79688
89	94	92.0729	83.0833	8.98958	1.92708
90	73	81.1198	83	-1.88021	-8.11979
91	81	78.2865	83.1667	-4.88021	2.71354
92	77	78.0625	83.375	-5.3125	-1.0625
93	105	97.3646	83.2083	14.1563	7.63542
94	74	76.1667	83.0417	-6.875	-2.16667
95	82	82.7448	83.0417	-0.296875	-0.744792
96	93	90.5938	82.9583	7.63542	2.40625
97	83	77.2656	82.7917	-5.52604	5.73438
98	66	72.7552	82.75	-9.99479	-6.75521
99	86	86.2708	82.8333	3.4375	-0.270833
100	83	83.2969	82.75	0.546875	-0.296875
101	93	91.6562	82.6667	8.98958	1.34375
102	72	80.7448	82.625	-1.88021	-8.74479
103	78	NA	NA	-4.88021	NA
104	79	NA	NA	-5.3125	NA
105	105	NA	NA	14.1563	NA
106	72	NA	NA	-6.875	NA
107	82	NA	NA	-0.296875	NA
108	92	NA	NA	7.63542	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 77 & NA & NA & -5.52604 & NA \tabularnewline
2 & 85 & NA & NA & -9.99479 & NA \tabularnewline
3 & 85 & NA & NA & 3.4375 & NA \tabularnewline
4 & 78 & NA & NA & 0.546875 & NA \tabularnewline
5 & 89 & NA & NA & 8.98958 & NA \tabularnewline
6 & 87 & NA & NA & -1.88021 & NA \tabularnewline
7 & 80 & 79.6198 & 84.5 & -4.88021 & 0.380208 \tabularnewline
8 & 83 & 79.2708 & 84.5833 & -5.3125 & 3.72917 \tabularnewline
9 & 88 & 98.6562 & 84.5 & 14.1563 & -10.6562 \tabularnewline
10 & 86 & 77.6667 & 84.5417 & -6.875 & 8.33333 \tabularnewline
11 & 81 & 84.4115 & 84.7083 & -0.296875 & -3.41146 \tabularnewline
12 & 94 & 92.3021 & 84.6667 & 7.63542 & 1.69792 \tabularnewline
13 & 79 & 79.1823 & 84.7083 & -5.52604 & -0.182292 \tabularnewline
14 & 85 & 75.0885 & 85.0833 & -9.99479 & 9.91146 \tabularnewline
15 & 83 & 89.0208 & 85.5833 & 3.4375 & -6.02083 \tabularnewline
16 & 81 & 86.1302 & 85.5833 & 0.546875 & -5.13021 \tabularnewline
17 & 90 & 94.3646 & 85.375 & 8.98958 & -4.36458 \tabularnewline
18 & 85 & 83.4115 & 85.2917 & -1.88021 & 1.58854 \tabularnewline
19 & 83 & 80.3281 & 85.2083 & -4.88021 & 2.67188 \tabularnewline
20 & 89 & 79.9792 & 85.2917 & -5.3125 & 9.02083 \tabularnewline
21 & 94 & 99.6562 & 85.5 & 14.1563 & -5.65625 \tabularnewline
22 & 80 & 79.0417 & 85.9167 & -6.875 & 0.958333 \tabularnewline
23 & 82 & 85.9115 & 86.2083 & -0.296875 & -3.91146 \tabularnewline
24 & 91 & 94.0104 & 86.375 & 7.63542 & -3.01042 \tabularnewline
25 & 80 & 80.724 & 86.25 & -5.52604 & -0.723958 \tabularnewline
26 & 86 & 75.5885 & 85.5833 & -9.99479 & 10.4115 \tabularnewline
27 & 87 & 88.8125 & 85.375 & 3.4375 & -1.8125 \tabularnewline
28 & 87 & 86.0469 & 85.5 & 0.546875 & 0.953125 \tabularnewline
29 & 91 & 94.6562 & 85.6667 & 8.98958 & -3.65625 \tabularnewline
30 & 88 & 84.0365 & 85.9167 & -1.88021 & 3.96354 \tabularnewline
31 & 77 & 80.8698 & 85.75 & -4.88021 & -3.86979 \tabularnewline
32 & 79 & 80.0625 & 85.375 & -5.3125 & -1.0625 \tabularnewline
33 & 99 & 99.3646 & 85.2083 & 14.1563 & -0.364583 \tabularnewline
34 & 78 & 78.4167 & 85.2917 & -6.875 & -0.416667 \tabularnewline
35 & 88 & 85.0365 & 85.3333 & -0.296875 & 2.96354 \tabularnewline
36 & 91 & 93.0938 & 85.4583 & 7.63542 & -2.09375 \tabularnewline
37 & 76 & 80.1406 & 85.6667 & -5.52604 & -4.14062 \tabularnewline
38 & 81 & 75.7552 & 85.75 & -9.99479 & 5.24479 \tabularnewline
39 & 88 & 89.1042 & 85.6667 & 3.4375 & -1.10417 \tabularnewline
40 & 88 & 86.0885 & 85.5417 & 0.546875 & 1.91146 \tabularnewline
41 & 91 & 94.4062 & 85.4167 & 8.98958 & -3.40625 \tabularnewline
42 & 91 & 83.5365 & 85.4167 & -1.88021 & 7.46354 \tabularnewline
43 & 79 & 80.5365 & 85.4167 & -4.88021 & -1.53646 \tabularnewline
44 & 79 & 79.7292 & 85.0417 & -5.3125 & -0.729167 \tabularnewline
45 & 97 & 98.9062 & 84.75 & 14.1563 & -1.90625 \tabularnewline
46 & 77 & 77.7917 & 84.6667 & -6.875 & -0.791667 \tabularnewline
47 & 86 & 84.4115 & 84.7083 & -0.296875 & 1.58854 \tabularnewline
48 & 93 & 92.3437 & 84.7083 & 7.63542 & 0.65625 \tabularnewline
49 & 74 & 79.1406 & 84.6667 & -5.52604 & -5.14062 \tabularnewline
50 & 74 & 74.5885 & 84.5833 & -9.99479 & -0.588542 \tabularnewline
51 & 88 & 87.9792 & 84.5417 & 3.4375 & 0.0208333 \tabularnewline
52 & 86 & 85.1719 & 84.625 & 0.546875 & 0.828125 \tabularnewline
53 & 94 & 93.5729 & 84.5833 & 8.98958 & 0.427083 \tabularnewline
54 & 88 & 82.6198 & 84.5 & -1.88021 & 5.38021 \tabularnewline
55 & 81 & 79.7448 & 84.625 & -4.88021 & 1.25521 \tabularnewline
56 & 75 & 79.3958 & 84.7083 & -5.3125 & -4.39583 \tabularnewline
57 & 100 & 98.6979 & 84.5417 & 14.1563 & 1.30208 \tabularnewline
58 & 76 & 77.625 & 84.5 & -6.875 & -1.625 \tabularnewline
59 & 86 & 84.3698 & 84.6667 & -0.296875 & 1.63021 \tabularnewline
60 & 91 & 92.2604 & 84.625 & 7.63542 & -1.26042 \tabularnewline
61 & 79 & 78.6823 & 84.2083 & -5.52604 & 0.317708 \tabularnewline
62 & 71 & 73.9635 & 83.9583 & -9.99479 & -2.96354 \tabularnewline
63 & 87 & 87.3125 & 83.875 & 3.4375 & -0.3125 \tabularnewline
64 & 86 & 84.2135 & 83.6667 & 0.546875 & 1.78646 \tabularnewline
65 & 98 & 92.3646 & 83.375 & 8.98958 & 5.63542 \tabularnewline
66 & 83 & 81.2865 & 83.1667 & -1.88021 & 1.71354 \tabularnewline
67 & 76 & 78.2031 & 83.0833 & -4.88021 & -2.20312 \tabularnewline
68 & 74 & 77.5208 & 82.8333 & -5.3125 & -3.52083 \tabularnewline
69 & 99 & 96.9062 & 82.75 & 14.1563 & 2.09375 \tabularnewline
70 & 72 & 76 & 82.875 & -6.875 & -4 \tabularnewline
71 & 83 & 82.3698 & 82.6667 & -0.296875 & 0.630208 \tabularnewline
72 & 89 & 89.9271 & 82.2917 & 7.63542 & -0.927083 \tabularnewline
73 & 79 & 76.6823 & 82.2083 & -5.52604 & 2.31771 \tabularnewline
74 & 65 & 72.4219 & 82.4167 & -9.99479 & -7.42188 \tabularnewline
75 & 91 & 86.1875 & 82.75 & 3.4375 & 4.8125 \tabularnewline
76 & 85 & 83.7135 & 83.1667 & 0.546875 & 1.28646 \tabularnewline
77 & 94 & 92.3646 & 83.375 & 8.98958 & 1.63542 \tabularnewline
78 & 78 & 81.7031 & 83.5833 & -1.88021 & -3.70312 \tabularnewline
79 & 79 & 78.8698 & 83.75 & -4.88021 & 0.130208 \tabularnewline
80 & 76 & 78.4375 & 83.75 & -5.3125 & -2.4375 \tabularnewline
81 & 105 & 97.9062 & 83.75 & 14.1563 & 7.09375 \tabularnewline
82 & 76 & 76.75 & 83.625 & -6.875 & -0.75 \tabularnewline
83 & 84 & 83.2031 & 83.5 & -0.296875 & 0.796875 \tabularnewline
84 & 93 & 90.9271 & 83.2917 & 7.63542 & 2.07292 \tabularnewline
85 & 79 & 77.6406 & 83.1667 & -5.52604 & 1.35938 \tabularnewline
86 & 65 & 73.2969 & 83.2917 & -9.99479 & -8.29688 \tabularnewline
87 & 91 & 86.7708 & 83.3333 & 3.4375 & 4.22917 \tabularnewline
88 & 82 & 83.7969 & 83.25 & 0.546875 & -1.79688 \tabularnewline
89 & 94 & 92.0729 & 83.0833 & 8.98958 & 1.92708 \tabularnewline
90 & 73 & 81.1198 & 83 & -1.88021 & -8.11979 \tabularnewline
91 & 81 & 78.2865 & 83.1667 & -4.88021 & 2.71354 \tabularnewline
92 & 77 & 78.0625 & 83.375 & -5.3125 & -1.0625 \tabularnewline
93 & 105 & 97.3646 & 83.2083 & 14.1563 & 7.63542 \tabularnewline
94 & 74 & 76.1667 & 83.0417 & -6.875 & -2.16667 \tabularnewline
95 & 82 & 82.7448 & 83.0417 & -0.296875 & -0.744792 \tabularnewline
96 & 93 & 90.5938 & 82.9583 & 7.63542 & 2.40625 \tabularnewline
97 & 83 & 77.2656 & 82.7917 & -5.52604 & 5.73438 \tabularnewline
98 & 66 & 72.7552 & 82.75 & -9.99479 & -6.75521 \tabularnewline
99 & 86 & 86.2708 & 82.8333 & 3.4375 & -0.270833 \tabularnewline
100 & 83 & 83.2969 & 82.75 & 0.546875 & -0.296875 \tabularnewline
101 & 93 & 91.6562 & 82.6667 & 8.98958 & 1.34375 \tabularnewline
102 & 72 & 80.7448 & 82.625 & -1.88021 & -8.74479 \tabularnewline
103 & 78 & NA & NA & -4.88021 & NA \tabularnewline
104 & 79 & NA & NA & -5.3125 & NA \tabularnewline
105 & 105 & NA & NA & 14.1563 & NA \tabularnewline
106 & 72 & NA & NA & -6.875 & NA \tabularnewline
107 & 82 & NA & NA & -0.296875 & NA \tabularnewline
108 & 92 & NA & NA & 7.63542 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296503&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]77[/C][C]NA[/C][C]NA[/C][C]-5.52604[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]85[/C][C]NA[/C][C]NA[/C][C]-9.99479[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]85[/C][C]NA[/C][C]NA[/C][C]3.4375[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]78[/C][C]NA[/C][C]NA[/C][C]0.546875[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]89[/C][C]NA[/C][C]NA[/C][C]8.98958[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]87[/C][C]NA[/C][C]NA[/C][C]-1.88021[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]80[/C][C]79.6198[/C][C]84.5[/C][C]-4.88021[/C][C]0.380208[/C][/ROW]
[ROW][C]8[/C][C]83[/C][C]79.2708[/C][C]84.5833[/C][C]-5.3125[/C][C]3.72917[/C][/ROW]
[ROW][C]9[/C][C]88[/C][C]98.6562[/C][C]84.5[/C][C]14.1563[/C][C]-10.6562[/C][/ROW]
[ROW][C]10[/C][C]86[/C][C]77.6667[/C][C]84.5417[/C][C]-6.875[/C][C]8.33333[/C][/ROW]
[ROW][C]11[/C][C]81[/C][C]84.4115[/C][C]84.7083[/C][C]-0.296875[/C][C]-3.41146[/C][/ROW]
[ROW][C]12[/C][C]94[/C][C]92.3021[/C][C]84.6667[/C][C]7.63542[/C][C]1.69792[/C][/ROW]
[ROW][C]13[/C][C]79[/C][C]79.1823[/C][C]84.7083[/C][C]-5.52604[/C][C]-0.182292[/C][/ROW]
[ROW][C]14[/C][C]85[/C][C]75.0885[/C][C]85.0833[/C][C]-9.99479[/C][C]9.91146[/C][/ROW]
[ROW][C]15[/C][C]83[/C][C]89.0208[/C][C]85.5833[/C][C]3.4375[/C][C]-6.02083[/C][/ROW]
[ROW][C]16[/C][C]81[/C][C]86.1302[/C][C]85.5833[/C][C]0.546875[/C][C]-5.13021[/C][/ROW]
[ROW][C]17[/C][C]90[/C][C]94.3646[/C][C]85.375[/C][C]8.98958[/C][C]-4.36458[/C][/ROW]
[ROW][C]18[/C][C]85[/C][C]83.4115[/C][C]85.2917[/C][C]-1.88021[/C][C]1.58854[/C][/ROW]
[ROW][C]19[/C][C]83[/C][C]80.3281[/C][C]85.2083[/C][C]-4.88021[/C][C]2.67188[/C][/ROW]
[ROW][C]20[/C][C]89[/C][C]79.9792[/C][C]85.2917[/C][C]-5.3125[/C][C]9.02083[/C][/ROW]
[ROW][C]21[/C][C]94[/C][C]99.6562[/C][C]85.5[/C][C]14.1563[/C][C]-5.65625[/C][/ROW]
[ROW][C]22[/C][C]80[/C][C]79.0417[/C][C]85.9167[/C][C]-6.875[/C][C]0.958333[/C][/ROW]
[ROW][C]23[/C][C]82[/C][C]85.9115[/C][C]86.2083[/C][C]-0.296875[/C][C]-3.91146[/C][/ROW]
[ROW][C]24[/C][C]91[/C][C]94.0104[/C][C]86.375[/C][C]7.63542[/C][C]-3.01042[/C][/ROW]
[ROW][C]25[/C][C]80[/C][C]80.724[/C][C]86.25[/C][C]-5.52604[/C][C]-0.723958[/C][/ROW]
[ROW][C]26[/C][C]86[/C][C]75.5885[/C][C]85.5833[/C][C]-9.99479[/C][C]10.4115[/C][/ROW]
[ROW][C]27[/C][C]87[/C][C]88.8125[/C][C]85.375[/C][C]3.4375[/C][C]-1.8125[/C][/ROW]
[ROW][C]28[/C][C]87[/C][C]86.0469[/C][C]85.5[/C][C]0.546875[/C][C]0.953125[/C][/ROW]
[ROW][C]29[/C][C]91[/C][C]94.6562[/C][C]85.6667[/C][C]8.98958[/C][C]-3.65625[/C][/ROW]
[ROW][C]30[/C][C]88[/C][C]84.0365[/C][C]85.9167[/C][C]-1.88021[/C][C]3.96354[/C][/ROW]
[ROW][C]31[/C][C]77[/C][C]80.8698[/C][C]85.75[/C][C]-4.88021[/C][C]-3.86979[/C][/ROW]
[ROW][C]32[/C][C]79[/C][C]80.0625[/C][C]85.375[/C][C]-5.3125[/C][C]-1.0625[/C][/ROW]
[ROW][C]33[/C][C]99[/C][C]99.3646[/C][C]85.2083[/C][C]14.1563[/C][C]-0.364583[/C][/ROW]
[ROW][C]34[/C][C]78[/C][C]78.4167[/C][C]85.2917[/C][C]-6.875[/C][C]-0.416667[/C][/ROW]
[ROW][C]35[/C][C]88[/C][C]85.0365[/C][C]85.3333[/C][C]-0.296875[/C][C]2.96354[/C][/ROW]
[ROW][C]36[/C][C]91[/C][C]93.0938[/C][C]85.4583[/C][C]7.63542[/C][C]-2.09375[/C][/ROW]
[ROW][C]37[/C][C]76[/C][C]80.1406[/C][C]85.6667[/C][C]-5.52604[/C][C]-4.14062[/C][/ROW]
[ROW][C]38[/C][C]81[/C][C]75.7552[/C][C]85.75[/C][C]-9.99479[/C][C]5.24479[/C][/ROW]
[ROW][C]39[/C][C]88[/C][C]89.1042[/C][C]85.6667[/C][C]3.4375[/C][C]-1.10417[/C][/ROW]
[ROW][C]40[/C][C]88[/C][C]86.0885[/C][C]85.5417[/C][C]0.546875[/C][C]1.91146[/C][/ROW]
[ROW][C]41[/C][C]91[/C][C]94.4062[/C][C]85.4167[/C][C]8.98958[/C][C]-3.40625[/C][/ROW]
[ROW][C]42[/C][C]91[/C][C]83.5365[/C][C]85.4167[/C][C]-1.88021[/C][C]7.46354[/C][/ROW]
[ROW][C]43[/C][C]79[/C][C]80.5365[/C][C]85.4167[/C][C]-4.88021[/C][C]-1.53646[/C][/ROW]
[ROW][C]44[/C][C]79[/C][C]79.7292[/C][C]85.0417[/C][C]-5.3125[/C][C]-0.729167[/C][/ROW]
[ROW][C]45[/C][C]97[/C][C]98.9062[/C][C]84.75[/C][C]14.1563[/C][C]-1.90625[/C][/ROW]
[ROW][C]46[/C][C]77[/C][C]77.7917[/C][C]84.6667[/C][C]-6.875[/C][C]-0.791667[/C][/ROW]
[ROW][C]47[/C][C]86[/C][C]84.4115[/C][C]84.7083[/C][C]-0.296875[/C][C]1.58854[/C][/ROW]
[ROW][C]48[/C][C]93[/C][C]92.3437[/C][C]84.7083[/C][C]7.63542[/C][C]0.65625[/C][/ROW]
[ROW][C]49[/C][C]74[/C][C]79.1406[/C][C]84.6667[/C][C]-5.52604[/C][C]-5.14062[/C][/ROW]
[ROW][C]50[/C][C]74[/C][C]74.5885[/C][C]84.5833[/C][C]-9.99479[/C][C]-0.588542[/C][/ROW]
[ROW][C]51[/C][C]88[/C][C]87.9792[/C][C]84.5417[/C][C]3.4375[/C][C]0.0208333[/C][/ROW]
[ROW][C]52[/C][C]86[/C][C]85.1719[/C][C]84.625[/C][C]0.546875[/C][C]0.828125[/C][/ROW]
[ROW][C]53[/C][C]94[/C][C]93.5729[/C][C]84.5833[/C][C]8.98958[/C][C]0.427083[/C][/ROW]
[ROW][C]54[/C][C]88[/C][C]82.6198[/C][C]84.5[/C][C]-1.88021[/C][C]5.38021[/C][/ROW]
[ROW][C]55[/C][C]81[/C][C]79.7448[/C][C]84.625[/C][C]-4.88021[/C][C]1.25521[/C][/ROW]
[ROW][C]56[/C][C]75[/C][C]79.3958[/C][C]84.7083[/C][C]-5.3125[/C][C]-4.39583[/C][/ROW]
[ROW][C]57[/C][C]100[/C][C]98.6979[/C][C]84.5417[/C][C]14.1563[/C][C]1.30208[/C][/ROW]
[ROW][C]58[/C][C]76[/C][C]77.625[/C][C]84.5[/C][C]-6.875[/C][C]-1.625[/C][/ROW]
[ROW][C]59[/C][C]86[/C][C]84.3698[/C][C]84.6667[/C][C]-0.296875[/C][C]1.63021[/C][/ROW]
[ROW][C]60[/C][C]91[/C][C]92.2604[/C][C]84.625[/C][C]7.63542[/C][C]-1.26042[/C][/ROW]
[ROW][C]61[/C][C]79[/C][C]78.6823[/C][C]84.2083[/C][C]-5.52604[/C][C]0.317708[/C][/ROW]
[ROW][C]62[/C][C]71[/C][C]73.9635[/C][C]83.9583[/C][C]-9.99479[/C][C]-2.96354[/C][/ROW]
[ROW][C]63[/C][C]87[/C][C]87.3125[/C][C]83.875[/C][C]3.4375[/C][C]-0.3125[/C][/ROW]
[ROW][C]64[/C][C]86[/C][C]84.2135[/C][C]83.6667[/C][C]0.546875[/C][C]1.78646[/C][/ROW]
[ROW][C]65[/C][C]98[/C][C]92.3646[/C][C]83.375[/C][C]8.98958[/C][C]5.63542[/C][/ROW]
[ROW][C]66[/C][C]83[/C][C]81.2865[/C][C]83.1667[/C][C]-1.88021[/C][C]1.71354[/C][/ROW]
[ROW][C]67[/C][C]76[/C][C]78.2031[/C][C]83.0833[/C][C]-4.88021[/C][C]-2.20312[/C][/ROW]
[ROW][C]68[/C][C]74[/C][C]77.5208[/C][C]82.8333[/C][C]-5.3125[/C][C]-3.52083[/C][/ROW]
[ROW][C]69[/C][C]99[/C][C]96.9062[/C][C]82.75[/C][C]14.1563[/C][C]2.09375[/C][/ROW]
[ROW][C]70[/C][C]72[/C][C]76[/C][C]82.875[/C][C]-6.875[/C][C]-4[/C][/ROW]
[ROW][C]71[/C][C]83[/C][C]82.3698[/C][C]82.6667[/C][C]-0.296875[/C][C]0.630208[/C][/ROW]
[ROW][C]72[/C][C]89[/C][C]89.9271[/C][C]82.2917[/C][C]7.63542[/C][C]-0.927083[/C][/ROW]
[ROW][C]73[/C][C]79[/C][C]76.6823[/C][C]82.2083[/C][C]-5.52604[/C][C]2.31771[/C][/ROW]
[ROW][C]74[/C][C]65[/C][C]72.4219[/C][C]82.4167[/C][C]-9.99479[/C][C]-7.42188[/C][/ROW]
[ROW][C]75[/C][C]91[/C][C]86.1875[/C][C]82.75[/C][C]3.4375[/C][C]4.8125[/C][/ROW]
[ROW][C]76[/C][C]85[/C][C]83.7135[/C][C]83.1667[/C][C]0.546875[/C][C]1.28646[/C][/ROW]
[ROW][C]77[/C][C]94[/C][C]92.3646[/C][C]83.375[/C][C]8.98958[/C][C]1.63542[/C][/ROW]
[ROW][C]78[/C][C]78[/C][C]81.7031[/C][C]83.5833[/C][C]-1.88021[/C][C]-3.70312[/C][/ROW]
[ROW][C]79[/C][C]79[/C][C]78.8698[/C][C]83.75[/C][C]-4.88021[/C][C]0.130208[/C][/ROW]
[ROW][C]80[/C][C]76[/C][C]78.4375[/C][C]83.75[/C][C]-5.3125[/C][C]-2.4375[/C][/ROW]
[ROW][C]81[/C][C]105[/C][C]97.9062[/C][C]83.75[/C][C]14.1563[/C][C]7.09375[/C][/ROW]
[ROW][C]82[/C][C]76[/C][C]76.75[/C][C]83.625[/C][C]-6.875[/C][C]-0.75[/C][/ROW]
[ROW][C]83[/C][C]84[/C][C]83.2031[/C][C]83.5[/C][C]-0.296875[/C][C]0.796875[/C][/ROW]
[ROW][C]84[/C][C]93[/C][C]90.9271[/C][C]83.2917[/C][C]7.63542[/C][C]2.07292[/C][/ROW]
[ROW][C]85[/C][C]79[/C][C]77.6406[/C][C]83.1667[/C][C]-5.52604[/C][C]1.35938[/C][/ROW]
[ROW][C]86[/C][C]65[/C][C]73.2969[/C][C]83.2917[/C][C]-9.99479[/C][C]-8.29688[/C][/ROW]
[ROW][C]87[/C][C]91[/C][C]86.7708[/C][C]83.3333[/C][C]3.4375[/C][C]4.22917[/C][/ROW]
[ROW][C]88[/C][C]82[/C][C]83.7969[/C][C]83.25[/C][C]0.546875[/C][C]-1.79688[/C][/ROW]
[ROW][C]89[/C][C]94[/C][C]92.0729[/C][C]83.0833[/C][C]8.98958[/C][C]1.92708[/C][/ROW]
[ROW][C]90[/C][C]73[/C][C]81.1198[/C][C]83[/C][C]-1.88021[/C][C]-8.11979[/C][/ROW]
[ROW][C]91[/C][C]81[/C][C]78.2865[/C][C]83.1667[/C][C]-4.88021[/C][C]2.71354[/C][/ROW]
[ROW][C]92[/C][C]77[/C][C]78.0625[/C][C]83.375[/C][C]-5.3125[/C][C]-1.0625[/C][/ROW]
[ROW][C]93[/C][C]105[/C][C]97.3646[/C][C]83.2083[/C][C]14.1563[/C][C]7.63542[/C][/ROW]
[ROW][C]94[/C][C]74[/C][C]76.1667[/C][C]83.0417[/C][C]-6.875[/C][C]-2.16667[/C][/ROW]
[ROW][C]95[/C][C]82[/C][C]82.7448[/C][C]83.0417[/C][C]-0.296875[/C][C]-0.744792[/C][/ROW]
[ROW][C]96[/C][C]93[/C][C]90.5938[/C][C]82.9583[/C][C]7.63542[/C][C]2.40625[/C][/ROW]
[ROW][C]97[/C][C]83[/C][C]77.2656[/C][C]82.7917[/C][C]-5.52604[/C][C]5.73438[/C][/ROW]
[ROW][C]98[/C][C]66[/C][C]72.7552[/C][C]82.75[/C][C]-9.99479[/C][C]-6.75521[/C][/ROW]
[ROW][C]99[/C][C]86[/C][C]86.2708[/C][C]82.8333[/C][C]3.4375[/C][C]-0.270833[/C][/ROW]
[ROW][C]100[/C][C]83[/C][C]83.2969[/C][C]82.75[/C][C]0.546875[/C][C]-0.296875[/C][/ROW]
[ROW][C]101[/C][C]93[/C][C]91.6562[/C][C]82.6667[/C][C]8.98958[/C][C]1.34375[/C][/ROW]
[ROW][C]102[/C][C]72[/C][C]80.7448[/C][C]82.625[/C][C]-1.88021[/C][C]-8.74479[/C][/ROW]
[ROW][C]103[/C][C]78[/C][C]NA[/C][C]NA[/C][C]-4.88021[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]79[/C][C]NA[/C][C]NA[/C][C]-5.3125[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]105[/C][C]NA[/C][C]NA[/C][C]14.1563[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]72[/C][C]NA[/C][C]NA[/C][C]-6.875[/C][C]NA[/C][/ROW]
[ROW][C]107[/C][C]82[/C][C]NA[/C][C]NA[/C][C]-0.296875[/C][C]NA[/C][/ROW]
[ROW][C]108[/C][C]92[/C][C]NA[/C][C]NA[/C][C]7.63542[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296503&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296503&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	77	NA	NA	-5.52604	NA
2	85	NA	NA	-9.99479	NA
3	85	NA	NA	3.4375	NA
4	78	NA	NA	0.546875	NA
5	89	NA	NA	8.98958	NA
6	87	NA	NA	-1.88021	NA
7	80	79.6198	84.5	-4.88021	0.380208
8	83	79.2708	84.5833	-5.3125	3.72917
9	88	98.6562	84.5	14.1563	-10.6562
10	86	77.6667	84.5417	-6.875	8.33333
11	81	84.4115	84.7083	-0.296875	-3.41146
12	94	92.3021	84.6667	7.63542	1.69792
13	79	79.1823	84.7083	-5.52604	-0.182292
14	85	75.0885	85.0833	-9.99479	9.91146
15	83	89.0208	85.5833	3.4375	-6.02083
16	81	86.1302	85.5833	0.546875	-5.13021
17	90	94.3646	85.375	8.98958	-4.36458
18	85	83.4115	85.2917	-1.88021	1.58854
19	83	80.3281	85.2083	-4.88021	2.67188
20	89	79.9792	85.2917	-5.3125	9.02083
21	94	99.6562	85.5	14.1563	-5.65625
22	80	79.0417	85.9167	-6.875	0.958333
23	82	85.9115	86.2083	-0.296875	-3.91146
24	91	94.0104	86.375	7.63542	-3.01042
25	80	80.724	86.25	-5.52604	-0.723958
26	86	75.5885	85.5833	-9.99479	10.4115
27	87	88.8125	85.375	3.4375	-1.8125
28	87	86.0469	85.5	0.546875	0.953125
29	91	94.6562	85.6667	8.98958	-3.65625
30	88	84.0365	85.9167	-1.88021	3.96354
31	77	80.8698	85.75	-4.88021	-3.86979
32	79	80.0625	85.375	-5.3125	-1.0625
33	99	99.3646	85.2083	14.1563	-0.364583
34	78	78.4167	85.2917	-6.875	-0.416667
35	88	85.0365	85.3333	-0.296875	2.96354
36	91	93.0938	85.4583	7.63542	-2.09375
37	76	80.1406	85.6667	-5.52604	-4.14062
38	81	75.7552	85.75	-9.99479	5.24479
39	88	89.1042	85.6667	3.4375	-1.10417
40	88	86.0885	85.5417	0.546875	1.91146
41	91	94.4062	85.4167	8.98958	-3.40625
42	91	83.5365	85.4167	-1.88021	7.46354
43	79	80.5365	85.4167	-4.88021	-1.53646
44	79	79.7292	85.0417	-5.3125	-0.729167
45	97	98.9062	84.75	14.1563	-1.90625
46	77	77.7917	84.6667	-6.875	-0.791667
47	86	84.4115	84.7083	-0.296875	1.58854
48	93	92.3437	84.7083	7.63542	0.65625
49	74	79.1406	84.6667	-5.52604	-5.14062
50	74	74.5885	84.5833	-9.99479	-0.588542
51	88	87.9792	84.5417	3.4375	0.0208333
52	86	85.1719	84.625	0.546875	0.828125
53	94	93.5729	84.5833	8.98958	0.427083
54	88	82.6198	84.5	-1.88021	5.38021
55	81	79.7448	84.625	-4.88021	1.25521
56	75	79.3958	84.7083	-5.3125	-4.39583
57	100	98.6979	84.5417	14.1563	1.30208
58	76	77.625	84.5	-6.875	-1.625
59	86	84.3698	84.6667	-0.296875	1.63021
60	91	92.2604	84.625	7.63542	-1.26042
61	79	78.6823	84.2083	-5.52604	0.317708
62	71	73.9635	83.9583	-9.99479	-2.96354
63	87	87.3125	83.875	3.4375	-0.3125
64	86	84.2135	83.6667	0.546875	1.78646
65	98	92.3646	83.375	8.98958	5.63542
66	83	81.2865	83.1667	-1.88021	1.71354
67	76	78.2031	83.0833	-4.88021	-2.20312
68	74	77.5208	82.8333	-5.3125	-3.52083
69	99	96.9062	82.75	14.1563	2.09375
70	72	76	82.875	-6.875	-4
71	83	82.3698	82.6667	-0.296875	0.630208
72	89	89.9271	82.2917	7.63542	-0.927083
73	79	76.6823	82.2083	-5.52604	2.31771
74	65	72.4219	82.4167	-9.99479	-7.42188
75	91	86.1875	82.75	3.4375	4.8125
76	85	83.7135	83.1667	0.546875	1.28646
77	94	92.3646	83.375	8.98958	1.63542
78	78	81.7031	83.5833	-1.88021	-3.70312
79	79	78.8698	83.75	-4.88021	0.130208
80	76	78.4375	83.75	-5.3125	-2.4375
81	105	97.9062	83.75	14.1563	7.09375
82	76	76.75	83.625	-6.875	-0.75
83	84	83.2031	83.5	-0.296875	0.796875
84	93	90.9271	83.2917	7.63542	2.07292
85	79	77.6406	83.1667	-5.52604	1.35938
86	65	73.2969	83.2917	-9.99479	-8.29688
87	91	86.7708	83.3333	3.4375	4.22917
88	82	83.7969	83.25	0.546875	-1.79688
89	94	92.0729	83.0833	8.98958	1.92708
90	73	81.1198	83	-1.88021	-8.11979
91	81	78.2865	83.1667	-4.88021	2.71354
92	77	78.0625	83.375	-5.3125	-1.0625
93	105	97.3646	83.2083	14.1563	7.63542
94	74	76.1667	83.0417	-6.875	-2.16667
95	82	82.7448	83.0417	-0.296875	-0.744792
96	93	90.5938	82.9583	7.63542	2.40625
97	83	77.2656	82.7917	-5.52604	5.73438
98	66	72.7552	82.75	-9.99479	-6.75521
99	86	86.2708	82.8333	3.4375	-0.270833
100	83	83.2969	82.75	0.546875	-0.296875
101	93	91.6562	82.6667	8.98958	1.34375
102	72	80.7448	82.625	-1.88021	-8.74479
103	78	NA	NA	-4.88021	NA
104	79	NA	NA	-5.3125	NA
105	105	NA	NA	14.1563	NA
106	72	NA	NA	-6.875	NA
107	82	NA	NA	-0.296875	NA
108	92	NA	NA	7.63542	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code